A valve positioner returns a 4–20 mA feedback signal while the PLC command is held at 90%. The measured feedback is 18.4 mA. This page owns that exact calculation job and opens the matching server-graded case rather than a generic calculator.
Follow the workflow
The lower range value is 0 and the upper range value is 100 % open. The engineering span is the difference between those values; it is not automatically zero-based.
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Open the registered Control-valve position transmitter case so the grader—not the browser copy—owns the expected result.
Open the exerciseSubtract the 4 mA live zero from 18.4 mA, then divide by the 16 mA measurement span. Keep enough precision until the engineering conversion is complete.
Do this in the product
Calculate the fraction separately before typing the final engineering value into the lab.
Open the exerciseMultiply percent span by the configured engineering span, then add 0 % open. The registered expected result is 90 % open within ±0.1%.
Do this in the product
Submit the value and inspect the range, live-zero and tolerance checks returned by the server.
Open the exerciseA calculation mismatch can come from signal measurement, transmitter configuration, PLC card range, program scaling or unit conversion. Preserve the measured current, range, result and timestamp before changing any layer.
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Create an account to retain the attempt, then use a paid workspace to compare cases, keep full history and assign the exercise.
Open the exerciseCore concepts
The simulator creates a repeatable result; these concepts make that result transferable to real vendor software and supervised practical work.
Four milliamps represents the lower engineering value, leaving near-zero current available as fault evidence.
For this Control-valve position transmitter, the span is 100 % open.
The case records the input, expected value, units and ±0.1% acceptance statement instead of returning an unexplained number.
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Run the foundation exercise publicly, then use a subscription for advanced challenges, saved configurations, full attempt history, sharing, assigned paths and team reporting.
Related learning surfaces
Competency and practice field guide
Direct answer
0–100 percent control-valve position exercise becomes useful when it connects command range, loop output, action direction, positioner input, supply pressure, zero and span, travel feedback, tolerance, hysteresis and process isolation with 0–100 percent request through analog output, loop current, positioner, actuator travel, position feedback and independent process indication, then proves declared points in both directions reach stable travel within tolerance with coherent current, command and feedback under normal, boundary, fault and recovery conditions. The objective is a repeatable engineering or learning result, not merely activity inside a page or tool.
This guide is written for instrumentation learners checking a valve command and feedback across a declared 0–100 percent travel range. The intended result is specific: the learner can scale output and feedback, test rising and falling points, quantify deviation and distinguish electrical, pneumatic and mechanical failures.
System map / 02
Treat these as connected checkpoints. Each checkpoint has an expected state, an observable state and a boundary to the next part of the system. That structure prevents a software indication from being mistaken for physical proof.
command range, loop output, action direction, positioner input, supply pressure, zero and span, travel feedback, tolerance, hysteresis and process isolation. For control-valve command scaling, position feedback, travel tolerance and process proof, record the initial condition, actor, requested change, observable result and stopping condition before selecting a tool or implementation.
0–100 percent request through analog output, loop current, positioner, actuator travel, position feedback and independent process indication. Separate request, internal state, output or service, physical or user-visible result and independent feedback so each boundary can be inspected.
declared points in both directions reach stable travel within tolerance with coherent current, command and feedback. Run more than one cycle from a known state and retain the values, timings or artifacts that demonstrate repeatability.
air loss, reversed action, sticky stem, deadband, saturated output, failed feedback, manual override, split range, restart and mechanical limit. Choose minimum, maximum, simultaneous, delayed or restart conditions that reveal assumptions hidden by the happy path.
a request, output scale, loop, positioner, air, actuator, travel, feedback, tolerance or process mismatch. Preserve the first symptom, divide the system at a measurable boundary and change one condition only after predicting the result.
the test completed with approved isolation, exact manufacturer procedure and independent process safeguards. Restore normal state, remove temporary changes, repeat affected checks and document which claims remain limited to the learning environment.
Procedure / 03
Run the steps in order the first time. Later, the same structure becomes a diagnostic loop: define the expected condition, observe the boundary, interpret the difference and choose one proving action.
Convert command range, loop output, action direction, positioner input, supply pressure, zero and span, travel feedback, tolerance, hysteresis and process isolation into initial conditions, one stimulus and observable pass criteria.
Evidence: Another person can repeat the case without guessing the intended result.
Avoid: Using page completion or an animation as the acceptance criterion.
Document 0–100 percent request through analog output, loop current, positioner, actuator travel, position feedback and independent process indication and name who owns each state or decision.
Evidence: Every request and result has a source, destination and useful inspection point.
Avoid: Using the same value as command, status and independent feedback.
Apply declared points in both directions reach stable travel within tolerance with coherent current, command and feedback from a clean start and record the expected evidence.
Evidence: Repeated runs produce the same bounded result.
Avoid: Changing several parameters before a baseline exists.
Test air loss, reversed action, sticky stem, deadband, saturated output, failed feedback, manual override, split range, restart and mechanical limit without changing the acceptance contract.
Evidence: Limits, timing and restart behavior reach defined states.
Avoid: Testing only one ideal sequence.
Introduce or analyse a request, output scale, loop, positioner, air, actuator, travel, feedback, tolerance or process mismatch and locate the first disagreement.
Evidence: The proving action distinguishes the leading hypotheses.
Avoid: Resetting, forcing or replacing before evidence is retained.
Complete the test completed with approved isolation, exact manufacturer procedure and independent process safeguards and repeat the affected regression cases.
Evidence: A learner completes the surface by explaining the result, passing a changed case and identifying what still requires supervised target-equipment practice.
Avoid: Treating an acknowledged message or one successful rerun as handover.
Diagnostic matrix / 04
The table is a reasoning aid, not a parts-replacement chart. Preserve the initial symptom, inspect the named boundary and use the interpretation to choose the next controlled test. Site safety procedures and equipment manuals remain authoritative.
| Observed symptom | Inspect | Interpretation | Next proving action |
|---|---|---|---|
| The expected result is unclear | Requirement, initial state, actor, stimulus, units and pass condition | The learner, instructor and assessor may be solving different versions of the task. | Rewrite one observable acceptance case before continuing. |
| Internal state changes but the outcome does not | Request, final owner, output or service boundary and independent feedback | A software or interface indication proves intent at one layer, not the complete outcome. | Trace the first boundary after the changing state. |
| Normal case passes but an edge case fails | Limits, timing, simultaneous events, reset and restart assumptions | The implementation contains a hidden assumption exposed by the changed condition. | Add the failed boundary as a permanent regression case. |
| The failure disappears after reset | Original symptom, histories, diagnostics, timestamps and active cause | Reset changed evidence or state without proving the initiating cause. | Reproduce under a controlled condition and preserve pre/post-event data. |
| Simulator and target disagree | Model boundary, software version, task timing, I/O behavior, data types and configuration | A learning model and the intended target do not share one of the recorded assumptions. | Reduce the case and verify against current target documentation. |
| The result cannot be explained | Prediction, observation, proving action, alternative hypotheses and limitations | Activity occurred but the evidence is not yet transferable or reviewable. | Have the learner defend the signal path and repeat a changed case. |
Product evidence / 05
The browser platform can retain programs, scenario results, attempts and observable machine state so practice is attached to evidence rather than seat time alone.
The exercise does not size a valve, authorize stroking connected equipment, define fail position, calibrate a positioner or prove actual process flow.
Commissioning notebook / 06
Use these as written briefs rather than click-through instructions. For every case, state the expected condition before acting, retain the first useful observation and explain why the final result proves the requirement. A different program or component choice can still be correct when it produces the same bounded behavior and evidence.
Case 01
predict → observe → prove
Engineering context. command range, loop output, action direction, positioner input, supply pressure, zero and span, travel feedback, tolerance, hysteresis and process isolation. For control-valve command scaling, position feedback, travel tolerance and process proof, record the initial condition, actor, requested change, observable result and stopping condition before selecting a tool or implementation. Begin with a written normal condition and identify which request, state, physical result or communication value will provide independent confirmation. Do not begin by changing the configuration; the initial state is part of the evidence and should remain reproducible.
Controlled setup. Use the “Write the acceptance case” stage of the workflow: convert command range, loop output, action direction, positioner input, supply pressure, zero and span, travel feedback, tolerance, hysteresis and process isolation into initial conditions, one stimulus and observable pass criteria. The acceptance record should show this result: another person can repeat the case without guessing the intended result. Record initial conditions, the exact stimulus and the observation point so another learner can repeat the case without relying on your memory.
Fault challenge. Introduce or analyse “The expected result is unclear” as one bounded deviation. Inspect requirement, initial state, actor, stimulus, units and pass condition The working interpretation is that the learner, instructor and assessor may be solving different versions of the task. The next proving action is to rewrite one observable acceptance case before continuing. Change only one condition before observing the result, and preserve timestamps or measurements where timing matters.
Review and recovery. The most common trap here is using page completion or an animation as the acceptance criterion. After restoring the cause, repeat the normal case and at least one stop, timeout, disconnect or restart boundary relevant to this topic. Remove temporary forces and bypasses, return the model to a known state and retain the evidence that both operation and recovery are deliberate.
Explain it aloud: How do you test a 0–100 percent control-valve position signal? A defensible short answer is: Apply authorized bounded command points in both directions and compare raw output, loop current, indicated travel and independent physical position within a declared tolerance.
Case 02
predict → observe → prove
Engineering context. 0–100 percent request through analog output, loop current, positioner, actuator travel, position feedback and independent process indication. Separate request, internal state, output or service, physical or user-visible result and independent feedback so each boundary can be inspected. Begin with a written normal condition and identify which request, state, physical result or communication value will provide independent confirmation. Do not begin by changing the configuration; the initial state is part of the evidence and should remain reproducible.
Controlled setup. Use the “Build the map” stage of the workflow: document 0–100 percent request through analog output, loop current, positioner, actuator travel, position feedback and independent process indication and name who owns each state or decision. The acceptance record should show this result: every request and result has a source, destination and useful inspection point. Record initial conditions, the exact stimulus and the observation point so another learner can repeat the case without relying on your memory.
Fault challenge. Introduce or analyse “Internal state changes but the outcome does not” as one bounded deviation. Inspect request, final owner, output or service boundary and independent feedback The working interpretation is that a software or interface indication proves intent at one layer, not the complete outcome. The next proving action is to trace the first boundary after the changing state. Change only one condition before observing the result, and preserve timestamps or measurements where timing matters.
Review and recovery. The most common trap here is using the same value as command, status and independent feedback. After restoring the cause, repeat the normal case and at least one stop, timeout, disconnect or restart boundary relevant to this topic. Remove temporary forces and bypasses, return the model to a known state and retain the evidence that both operation and recovery are deliberate.
Explain it aloud: Does 50 percent valve travel mean 50 percent flow? A defensible short answer is: Not necessarily. Flow depends on valve characteristic, pressure conditions and system resistance; travel feedback proves position, not linear process flow.
Case 03
predict → observe → prove
Engineering context. declared points in both directions reach stable travel within tolerance with coherent current, command and feedback. Run more than one cycle from a known state and retain the values, timings or artifacts that demonstrate repeatability. Begin with a written normal condition and identify which request, state, physical result or communication value will provide independent confirmation. Do not begin by changing the configuration; the initial state is part of the evidence and should remain reproducible.
Controlled setup. Use the “Run the baseline” stage of the workflow: apply declared points in both directions reach stable travel within tolerance with coherent current, command and feedback from a clean start and record the expected evidence. The acceptance record should show this result: repeated runs produce the same bounded result. Record initial conditions, the exact stimulus and the observation point so another learner can repeat the case without relying on your memory.
Fault challenge. Introduce or analyse “Normal case passes but an edge case fails” as one bounded deviation. Inspect limits, timing, simultaneous events, reset and restart assumptions The working interpretation is that the implementation contains a hidden assumption exposed by the changed condition. The next proving action is to add the failed boundary as a permanent regression case. Change only one condition before observing the result, and preserve timestamps or measurements where timing matters.
Review and recovery. The most common trap here is changing several parameters before a baseline exists. After restoring the cause, repeat the normal case and at least one stop, timeout, disconnect or restart boundary relevant to this topic. Remove temporary forces and bypasses, return the model to a known state and retain the evidence that both operation and recovery are deliberate.
Explain it aloud: What should I learn first about control-valve command scaling, position feedback, travel tolerance and process proof? A defensible short answer is: Start with the operating contract and evidence path: command range, loop output, action direction, positioner input, supply pressure, zero and span, travel feedback, tolerance, hysteresis and process isolation, followed by 0–100 percent request through analog output, loop current, positioner, actuator travel, position feedback and independent process indication. Add advanced features only after the baseline is predictable.
Case 04
predict → observe → prove
Engineering context. air loss, reversed action, sticky stem, deadband, saturated output, failed feedback, manual override, split range, restart and mechanical limit. Choose minimum, maximum, simultaneous, delayed or restart conditions that reveal assumptions hidden by the happy path. Begin with a written normal condition and identify which request, state, physical result or communication value will provide independent confirmation. Do not begin by changing the configuration; the initial state is part of the evidence and should remain reproducible.
Controlled setup. Use the “Challenge assumptions” stage of the workflow: test air loss, reversed action, sticky stem, deadband, saturated output, failed feedback, manual override, split range, restart and mechanical limit without changing the acceptance contract. The acceptance record should show this result: limits, timing and restart behavior reach defined states. Record initial conditions, the exact stimulus and the observation point so another learner can repeat the case without relying on your memory.
Fault challenge. Introduce or analyse “The failure disappears after reset” as one bounded deviation. Inspect original symptom, histories, diagnostics, timestamps and active cause The working interpretation is that reset changed evidence or state without proving the initiating cause. The next proving action is to reproduce under a controlled condition and preserve pre/post-event data. Change only one condition before observing the result, and preserve timestamps or measurements where timing matters.
Review and recovery. The most common trap here is testing only one ideal sequence. After restoring the cause, repeat the normal case and at least one stop, timeout, disconnect or restart boundary relevant to this topic. Remove temporary forces and bypasses, return the model to a known state and retain the evidence that both operation and recovery are deliberate.
Explain it aloud: How do I practise control-valve command scaling, position feedback, travel tolerance and process proof effectively? A defensible short answer is: Use short cases with known initial conditions, a written prediction, one action and an observable result. Then alter a boundary or fault and explain why the evidence changed.
Case 05
predict → observe → prove
Engineering context. a request, output scale, loop, positioner, air, actuator, travel, feedback, tolerance or process mismatch. Preserve the first symptom, divide the system at a measurable boundary and change one condition only after predicting the result. Begin with a written normal condition and identify which request, state, physical result or communication value will provide independent confirmation. Do not begin by changing the configuration; the initial state is part of the evidence and should remain reproducible.
Controlled setup. Use the “Isolate one failure” stage of the workflow: introduce or analyse a request, output scale, loop, positioner, air, actuator, travel, feedback, tolerance or process mismatch and locate the first disagreement. The acceptance record should show this result: the proving action distinguishes the leading hypotheses. Record initial conditions, the exact stimulus and the observation point so another learner can repeat the case without relying on your memory.
Fault challenge. Introduce or analyse “Simulator and target disagree” as one bounded deviation. Inspect model boundary, software version, task timing, I/O behavior, data types and configuration The working interpretation is that a learning model and the intended target do not share one of the recorded assumptions. The next proving action is to reduce the case and verify against current target documentation. Change only one condition before observing the result, and preserve timestamps or measurements where timing matters.
Review and recovery. The most common trap here is resetting, forcing or replacing before evidence is retained. After restoring the cause, repeat the normal case and at least one stop, timeout, disconnect or restart boundary relevant to this topic. Remove temporary forces and bypasses, return the model to a known state and retain the evidence that both operation and recovery are deliberate.
Explain it aloud: What counts as proof of competence? A defensible short answer is: A repeatable artifact or system result plus an explanation of the signal path is stronger than time spent, screenshots or a copied answer. Physical competence requires separate supervised evidence.
Case 06
predict → observe → prove
Engineering context. the test completed with approved isolation, exact manufacturer procedure and independent process safeguards. Restore normal state, remove temporary changes, repeat affected checks and document which claims remain limited to the learning environment. Begin with a written normal condition and identify which request, state, physical result or communication value will provide independent confirmation. Do not begin by changing the configuration; the initial state is part of the evidence and should remain reproducible.
Controlled setup. Use the “Close the evidence loop” stage of the workflow: complete the test completed with approved isolation, exact manufacturer procedure and independent process safeguards and repeat the affected regression cases. The acceptance record should show this result: a learner completes the surface by explaining the result, passing a changed case and identifying what still requires supervised target-equipment practice. Record initial conditions, the exact stimulus and the observation point so another learner can repeat the case without relying on your memory.
Fault challenge. Introduce or analyse “The result cannot be explained” as one bounded deviation. Inspect prediction, observation, proving action, alternative hypotheses and limitations The working interpretation is that activity occurred but the evidence is not yet transferable or reviewable. The next proving action is to have the learner defend the signal path and repeat a changed case. Change only one condition before observing the result, and preserve timestamps or measurements where timing matters.
Review and recovery. The most common trap here is treating an acknowledged message or one successful rerun as handover. After restoring the cause, repeat the normal case and at least one stop, timeout, disconnect or restart boundary relevant to this topic. Remove temporary forces and bypasses, return the model to a known state and retain the evidence that both operation and recovery are deliberate.
Explain it aloud: Why test faults and restart behavior? A defensible short answer is: Because a request, output scale, loop, positioner, air, actuator, travel, feedback, tolerance or process mismatch or air loss, reversed action, sticky stem, deadband, saturated output, failed feedback, manual override, split range, restart and mechanical limit can expose assumptions that never appear during ideal startup and steady operation.
Answer surface / 07
These concise answers define the operating, training and product boundaries most often missed in broad summaries. The full workflow and diagnostic table above provide the evidence behind them.
Apply authorized bounded command points in both directions and compare raw output, loop current, indicated travel and independent physical position within a declared tolerance.
Not necessarily. Flow depends on valve characteristic, pressure conditions and system resistance; travel feedback proves position, not linear process flow.
Start with the operating contract and evidence path: command range, loop output, action direction, positioner input, supply pressure, zero and span, travel feedback, tolerance, hysteresis and process isolation, followed by 0–100 percent request through analog output, loop current, positioner, actuator travel, position feedback and independent process indication. Add advanced features only after the baseline is predictable.
Use short cases with known initial conditions, a written prediction, one action and an observable result. Then alter a boundary or fault and explain why the evidence changed.
A repeatable artifact or system result plus an explanation of the signal path is stronger than time spent, screenshots or a copied answer. Physical competence requires separate supervised evidence.
Because a request, output scale, loop, positioner, air, actuator, travel, feedback, tolerance or process mismatch or air loss, reversed action, sticky stem, deadband, saturated output, failed feedback, manual override, split range, restart and mechanical limit can expose assumptions that never appear during ideal startup and steady operation.
No. It can build concepts and diagnostic reasoning. Exact firmware, I/O electrical behavior, networking, safety and commissioning require current official tools, documentation and target equipment.
Keep the requirement, initial state, program or configuration, observed values, fault hypothesis, proving action, recovery result and a concise limitations statement.
Continue the signal path / 08